The behavior patterns are examined for anomalies and conclusions are drawn about insider threats, malware deployment, and cybersecurity attacks by users. The target of UBA analyses are the users and their behavioral patterns, which are analyzed as accurately as possible through tracking and other monitoring techniques such as by analyzing transmission logs, network logs and authentication protocols. The data can be collected and stored in SIEM systems and analyzed for behavioral patterns to identify normal and malicious user behavior.
UBA systems work with large amounts of data, Big Data, and machine learning algorithms to assess deviations in near real-time. The systems provide actionable insights to security teams. The systems can be configured to automatically adjust the difficulty of authenticatingusers with anomalous behavior.